docs: def _construct_word_token(self, d: Dict, nlp) -> List[Dict]:
          """
          Construct a word token
          Args:
              d: Dict
              nlp
  
          Returns: List[Dict]
          """
  
          result = []
          if len(d["token"]) == 1:
              if tf_transfer(d["match_all_forms"]):
                  this_token = {attrs.LEMMA: nlp(d["token"][0])[0].lemma_}
              else:
                  this_token = {attrs.LOWER: d["token"][0].lower()}
              result.append(this_token)
              if d["capitalization"]:
                  result = self._add_capitalization_constrain(result, d["capitalization"], d["token"])
  
          elif not d["token"]:
              if tf_transfer(d["contain_digit"]):
                  this_token = {attrs.IS_ASCII: True, attrs.IS_PUNCT: False}
              else:
                  this_token = {attrs.IS_ALPHA: True}
              if tf_transfer(d["is_out_of_vocabulary"]) and not tf_transfer(d["is_in_vocabulary"]):
                  this_token[attrs.IS_OOV] = True
              elif not tf_transfer(d["is_out_of_vocabulary"]) and tf_transfer(d["is_in_vocabulary"]):
                  this_token[attrs.IS_OOV] = False
              result.append(this_token)
              if d["length"]:
                  result = self._add_length_constrain(result, d["length"])
              if d["capitalization"]:
                  result = self._add_capitalization_constrain(result, d["capitalization"], d["token"])
  
          else:
              if "match_all_forms" in d and not tf_transfer(d["match_all_forms"]):
                  global FLAG_ID
                  token_set = set(d["token"])
  
                  def is_selected_token(x):
                      return x in token_set
  
                  FLAG_DICT[FLAG_ID] = nlp.vocab.add_flag(is_selected_token)
                  this_token = {FLAG_DICT[FLAG_ID]: True}
                  FLAG_ID += 1
                  result.append(this_token)
  
              else:
                  token_set = [nlp(x)[0].lemma_ for x in set(d["token"])]
                  for a_lemma in token_set:
                      this_token = {attrs.LEMMA: a_lemma}
                      result.append(this_token)
  
              if d["capitalization"]:
                  result = self._add_capitalization_constrain(result, d["capitalization"], d["token"])
  
          result = self._add_common_constrain(result, d)
          if d["part_of_speech"]:
              result = self._add_pos_constrain(result, d["part_of_speech"])
  
          return result